PhD - Neurosymbolic Reasoning for Domain-Adaptive Generative AI
Core
Researching methods to adapt generative AI systems to specialized domains by integrating structured symbolic knowledge (knowledge graphs, ontologies) without extensive model retraining.
Role type
PhD researcher in neurosymbolic reasoning and domain-adaptive generative AI
Builds
Next-generation AI systems combining neural flexibility with symbolic reliability for hardware design assistance, verification, and code generation
Domain
Artificial Intelligence / Machine Learning / Electronic Hardware Design
Deliverable
research
Required skills
deep learning, graph algorithms, knowledge representation, computer science fundamentals
Preferred skills
electrical engineering, hardware design knowledge
Technologies
Large Language Models (LLMs), knowledge graphs, ontologies, formal design representations
